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@AISViz

AISViz: Making vessels tracking data available to everyone

We are a research initiative fromMERIDIAN (Marine Environmental Research Infrastructure for Data Integration and Application Network) hosted onMAPS (Modeling and Analytics on Predictive Systems) group atDalhousie University and funded by theDepartment of Fisheries and Oceans (DFO) of theGovernment of Canada. This project aims to facilitate usingAutomatic Identification System (AIS) data for marine vessel tracking to enhance our understanding of global maritime traffic and the impacts of vessel activity on marine ecosystems.

💡 Goals

Our main objective is to build an easy-to-use open-source toolbox for raw AIS data extraction, processing, visualization, and vessel modeling. We aim to make AIS data accessible and comprehensible for a broad spectrum of users, from government bodies and policymakers to university researchers, non-government organizations (NGOs), coastal communities, and the general public.

💻 Technicalities

AISviz was proposed to implement machine learning applications that work seamlessly with flexible data sources from terrestrial and satellite streams of AIS data. Besides, we intend to make the interaction with AIS data user-friendly, which will be achieved by developing a graphical user interface (GUI). This approach will simplify data retrieval, integration, and basic manipulation processes. We also aim to enhance AIS data's applicability by integrating it with different maritime raster-based third-party data sources. The project and all its components will be made openly accessible, promoting collaboration, transparency, and public contribution.

🚀 Contributions

Through AISviz, we aim to open new pathways of research and policy-making strategies related to environmental preservation, vessel traffic optimization, illegal fishing detection, aquatic invasive species prevention, noise pollution monitoring, and much more. Moreover, AISviz would equip anyone interested in understanding the patterns and impacts of vessel movement with the necessary tools and knowledge to do so. Even if you're just an enthusiast, educator, student, or concerned citizen, AISviz can help you grasp the crucial role of vessel traffic in shaping our world's oceans.

👥 Collaborations

This project was born out of active collaboration, and we're ready to widen our circle. Regardless of your offering or background - whether you are a seasoned researcher, a programmer interested in AIS data, an organization focusing on marine conservation, or an eager learner fascinated by ocean sciences – our project welcomes you! Feel free to connect with us. We're always ready to answer your questions, consider your suggestions, and engage in discussions regarding AIS data.

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  1. AISdbAISdbPublic

    AISdb Python package for smart AIS data storage and itegration.

    Python 44 10

  2. TutorialsTutorialsPublic

    Notebooks with tutorial examples.

    Jupyter Notebook 2 2

  3. NOAA-AIS-IntegratorNOAA-AIS-IntegratorPublic

    Acquisition and processing of AIS data from Marine Cadastre, with integration into an AISdb-aligned database.

    Python 2

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